# Imputing not available values in single‐cell DNA methylation data using the median is straightforward and effective

## TL;DR

This paper shows that using the median is a simple and effective way to handle missing data in single-cell DNA methylation studies.

## Contribution

The novelty lies in demonstrating through experiments and theory that median imputation is effective for NA values in single-cell DNA methylation data.

## Key findings

- Median imputation accurately reflects methylation states of missing values.
- Median imputation provides a solid foundation for downstream analyses.
- Theoretical and experimental evidence supports the effectiveness of median imputation.

## Abstract

Recent advances in single‐cell DNA methylation have provided unprecedented opportunities to explore cellular epigenetic differences with maximal resolution. A common workflow for single‐cell DNA methylation analysis is binning the genome into multiple regions and computing the average methylation level within each region. In this process, imputing not available (NA) values which are caused by the limited number of captured methylation sites is a necessary preprocessing step for downstream analyses. Existing studies have employed several simple imputation methods (such as zeros imputation or means imputation), however, there is a lack of theoretical studies or benchmark tests of these approaches. Through both experiments and theoretical analysis, we found that using the medians to impute NA values can effectively and simply reflect the methylation state of the NA values, providing an accurate foundation for downstream analyses.